Faster replay of metadata and data operations using inode number based dependency graph

ABSTRACT

Techniques are provided for replay of metadata and data operations. During initial execution of operations, identifiers of objects modified by the execution of each operation are identified and stored in association with the operations. When the operations are to be replayed (e.g., executed again, such as part of a replication operation or as part of flushing content from a cache to persistent storage), the identifiers are evaluated to determine which operations are independent with respect to one another and which operations are dependent with respect to one another. In this way, independent operations are executed in parallel and dependent operations are executed serially with respect to the operations from the dependent operations depend.

RELATED APPLICATIONS

This application claims priority to and is a continuation of U.S.application Ser. No. 15/945,178, filed on Apr. 4, 2018, now allowed,titled “FASTER REPLAY OF METADATA AND DATA OPERATIONS USING INODE NUMBERBASED DEPENDENCY GRAPH,” which is incorporated herein by reference.

BACKGROUND

A computing system, such as a client device, a storage environment, aserver, a distributed network, or a cloud computing environment,processes data operations and metadata operations. Data operationscomprise read operations to read data from objects such as files andwrite operations that write data to objects. Metadata operationscomprise other types of operations, such as create operations, linkoperations, unlink operations, set attribute operations, renameoperations, expand size operations, etc. The operations are executed bya file system of the computing system in a particular order, and thusobjects are modified by the executed operations in a particular order.

Two situations where the operations may be replayed (e.g., executedagain) are replication of the operations and replay of the operationsfrom a non-volatile random access memory (NVRAM) to a storage deviceafter a system panic. In one example, data of the computing device isreplicated to a second computing device, such as where data within aprimary volume hosted by the computing device is replicated to asecondary volume hosted by the second computing device. In particular,the computing device may locally implement incoming operations upon theprimary volume, and may replicate the incoming operations as replicatedoperations that are transmitted to the second computing device forreplay (e.g., for execution upon the secondary volume). Because thestate of the secondary volume should be consistent with the state of theprimary volume (e.g., the same data, file structure, etc.), the orderwith which the incoming operations were locally implemented (e.g., theorder with which the objects were modified by the operations) should bepreserved at the second computing device. This can be achieved byassigning sequence numbers to operations according to the order withwhich the operations were executed, and then serially executing thereplicated operations according to the sequence numbers. Otherwise, thesecondary volume will not be consistent with the primary volume.

In another example, incoming operations are executed upon the NVRAM andare tracked using a non-volatile log (NVLog) of a node. When a replaytriggering event occurs (e.g., the node panics, the node is taken overby a high availability partner node, the node boots up, etc.), theoperations tracked within the NVLog are replayed. The operations must bereplayed in the same order to ensure consistency.

Sequence numbers are used to enforce the replay order of operations. Thesequence numbers and certain rules are used to replay the operations ina manner that is consistent with the state of objects originallymodified by the initial execution of the operations. In some instances,data operations can be performed in parallel when the data operationsare independent of one another (e.g., a write operation to file 1 and awrite operation to file 2) while dependent data operations are performedserially (e.g., a first write operation to range 1 of the file 1 and asecond write operation to a range 2 of the file 1 that overlaps with therange 1). However, current replay techniques have technical limitationsof being unable to determine whether metadata operations are dependentor independent with respect to other operations. Thus, metadataoperations are performed serially and are mutually exclusive with writeoperations. Forcing metadata operations to be serially performed inorder to achieve consistency results in degrade operation of thecomputing system because client latency is significantly increased, thetime and computing resources used to replay operations is increased,etc. In one example, the decision to replay operations independently orserially may be performed at a volume level, and thus operationsdirected to two different volumes are already considered independentupon one another.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a component block diagram illustrating an example clusterednetwork in which an embodiment of the invention may be implemented.

FIG. 2 is a component block diagram illustrating an example data storagesystem in which an embodiment of the invention may be implemented.

FIG. 3 is a flow chart illustrating an example method for replayingmetadata and data operations.

FIG. 4 is a component block diagram illustrating an example system forreplaying metadata and data operations.

FIG. 5 is a component block diagram illustrating an example system forreplaying metadata and data operations as part of a replicationoperation.

FIG. 6 is an example of a computer readable medium in which anembodiment of the invention may be implemented.

FIG. 7 is a component block diagram illustrating an example computingenvironment in which an embodiment of the invention may be implemented.

DETAILED DESCRIPTION

Some examples of the claimed subject matter are now described withreference to the drawings, where like reference numerals are generallyused to refer to like elements throughout. In the following description,for purposes of explanation, numerous specific details are set forth inorder to provide an understanding of the claimed subject matter. It maybe evident, however, that the claimed subject matter may be practicedwithout these specific details. Nothing in this detailed description isadmitted as prior art.

One or more techniques and/or computing devices for replay of metadataand data operations are provided herein. This replay technique providesa technical solution to a technical problem deep rooted in computingtechnology of how to identify independent operations that can bereplayed in parallel and dependent operations that must be replayedserially. Conventional replay techniques are unable to determine whethermetadata operations are independent or dependent with respect to otheroperations, and thus are replayed serially and mutually exclusive towrite operations. This significantly increase the time to replayoperations, which can affect client latency and accessibility to data.

Accordingly, this replay technique provides significantly more thanconventional replay techniques by tracking what objects (e.g., files,inodes, directories, etc.) are affected (e.g., modified) by an initialexecution of a metadata operation. Thus, when the metadata operation isreplayed, the metadata operation may potentially be executed in parallelwith other operations that do not affect the same objects. In this way,operations can be replayed in a manner that provides data consistencyand reduces latency and resource usage otherwise wasted by onlyreplaying metadata operations in serial.

To provide for replay of metadata and data operations, FIG. 1illustrates an embodiment of a clustered network environment 100 or anetwork storage environment. It may be appreciated, however, that thetechniques, etc. described herein may be implemented within theclustered network environment 100, a non-cluster network environment,and/or a variety of other computing environments, such as a desktopcomputing environment. That is, the instant disclosure, including thescope of the appended claims, is not meant to be limited to the examplesprovided herein. It will be appreciated that where the same or similarcomponents, elements, features, items, modules, etc. are illustrated inlater figures but were previously discussed with regard to priorfigures, that a similar (e.g., redundant) discussion of the same may beomitted when describing the subsequent figures (e.g., for purposes ofsimplicity and ease of understanding).

FIG. 1 is a block diagram illustrating the clustered network environment100 that may implement at least some embodiments of the techniquesand/or systems described herein. The clustered network environment 100comprises data storage systems 102 and 104 that are coupled over acluster fabric 106, such as a computing network embodied as a privateInfiniband, Fibre Channel (FC), or Ethernet network facilitatingcommunication between the data storage systems 102 and 104 (and one ormore modules, component, etc. therein, such as, nodes 116 and 118, forexample). It will be appreciated that while two data storage systems 102and 104 and two nodes 116 and 118 are illustrated in FIG. 1, that anysuitable number of such components is contemplated. In an example, nodes116, 118 comprise storage controllers (e.g., node 116 may comprise aprimary or local storage controller and node 118 may comprise asecondary or remote storage controller) that provide client devices,such as host devices 108, 110, with access to data stored within datastorage devices 128, 130. Similarly, unless specifically providedotherwise herein, the same is true for other modules, elements,features, items, etc. referenced herein and/or illustrated in theaccompanying drawings. That is, a particular number of components,modules, elements, features, items, etc. disclosed herein is not meantto be interpreted in a limiting manner.

It will be further appreciated that clustered networks are not limitedto any particular geographic areas and can be clustered locally and/orremotely. Thus, in one embodiment a clustered network can be distributedover a plurality of storage systems and/or nodes located in a pluralityof geographic locations; while in another embodiment a clustered networkcan include data storage systems (e.g., 102, 104) residing in a samegeographic location (e.g., in a single onsite rack of data storagedevices).

In the illustrated example, one or more host devices 108, 110 which maycomprise, for example, client devices, personal computers (PCs),computing devices used for storage (e.g., storage servers), and othercomputers or peripheral devices (e.g., printers), are coupled to therespective data storage systems 102, 104 by storage network connections112, 114. Network connection may comprise a local area network (LAN) orwide area network (WAN), for example, that utilizes Network AttachedStorage (NAS) protocols, such as a Common Internet File System (CIFS)protocol or a Network File System (NFS) protocol to exchange datapackets, a Storage Area Network (SAN) protocol, such as Small ComputerSystem Interface (SCSI) or Fiber Channel Protocol (FCP), an objectprotocol, such as S3, etc. Illustratively, the host devices 108, 110 maybe general-purpose computers running applications, and may interact withthe data storage systems 102, 104 using a client/server model forexchange of information. That is, the host device may request data fromthe data storage system (e.g., data on a storage device managed by anetwork storage control configured to process I/O commands issued by thehost device for the storage device), and the data storage system mayreturn results of the request to the host device via one or more storagenetwork connections 112, 114.

The nodes 116, 118 on clustered data storage systems 102, 104 cancomprise network or host nodes that are interconnected as a cluster toprovide data storage and management services, such as to an enterprisehaving remote locations, cloud storage (e.g., a storage endpoint may bestored within a data cloud), etc., for example. Such a node in theclustered network environment 100 can be a device attached to thenetwork as a connection point, redistribution point or communicationendpoint, for example. A node may be capable of sending, receiving,and/or forwarding information over a network communications channel, andcould comprise any device that meets any or all of these criteria. Oneexample of a node may be a data storage and management server attachedto a network, where the server can comprise a general purpose computeror a computing device particularly configured to operate as a server ina data storage and management system.

In an example, a first cluster of nodes such as the nodes 116, 118(e.g., a first set of storage controllers configured to provide accessto a first storage aggregate comprising a first logical grouping of oneor more storage devices) may be located on a first storage site. Asecond cluster of nodes, not illustrated, may be located at a secondstorage site (e.g., a second set of storage controllers configured toprovide access to a second storage aggregate comprising a second logicalgrouping of one or more storage devices). The first cluster of nodes andthe second cluster of nodes may be configured according to a disasterrecovery configuration where a surviving cluster of nodes providesswitchover access to storage devices of a disaster cluster of nodes inthe event a disaster occurs at a disaster storage site comprising thedisaster cluster of nodes (e.g., the first cluster of nodes providesclient devices with switchover data access to storage devices of thesecond storage aggregate in the event a disaster occurs at the secondstorage site).

As illustrated in the clustered network environment 100, nodes 116, 118can comprise various functional components that coordinate to providedistributed storage architecture for the cluster. For example, the nodescan comprise network modules 120, 122 and disk modules 124, 126. Networkmodules 120, 122 can be configured to allow the nodes 116, 118 (e.g.,network storage controllers) to connect with host devices 108, 110 overthe storage network connections 112, 114, for example, allowing the hostdevices 108, 110 to access data stored in the distributed storagesystem. Further, the network modules 120, 122 can provide connectionswith one or more other components through the cluster fabric 106. Forexample, in FIG. 1, the network module 120 of node 116 can access asecond data storage device by sending a request through the disk module126 of node 118.

Disk modules 124, 126 can be configured to connect one or more datastorage devices 128, 130, such as disks or arrays of disks, flashmemory, or some other form of data storage, to the nodes 116, 118. Thenodes 116, 118 can be interconnected by the cluster fabric 106, forexample, allowing respective nodes in the cluster to access data on datastorage devices 128, 130 connected to different nodes in the cluster.Often, disk modules 124, 126 communicate with the data storage devices128, 130 according to the SAN protocol, such as SCSI or FCP, forexample. Thus, as seen from an operating system on nodes 116, 118, thedata storage devices 128, 130 can appear as locally attached to theoperating system. In this manner, different nodes 116, 118, etc. mayaccess data blocks through the operating system, rather than expresslyrequesting abstract files.

It should be appreciated that, while the clustered network environment100 illustrates an equal number of network and disk modules, otherembodiments may comprise a differing number of these modules. Forexample, there may be a plurality of network and disk modulesinterconnected in a cluster that does not have a one-to-onecorrespondence between the network and disk modules. That is, differentnodes can have a different number of network and disk modules, and thesame node can have a different number of network modules than diskmodules.

Further, a host device 108, 110 can be networked with the nodes 116, 118in the cluster, over the storage networking connections 112, 114. As anexample, respective host devices 108, 110 that are networked to acluster may request services (e.g., exchanging of information in theform of data packets) of nodes 116, 118 in the cluster, and the nodes116, 118 can return results of the requested services to the hostdevices 108, 110. In one embodiment, the host devices 108, 110 canexchange information with the network modules 120, 122 residing in thenodes 116, 118 (e.g., network hosts) in the data storage systems 102,104.

In one embodiment, the data storage devices 128, 130 comprise volumes132, which is an implementation of storage of information onto diskdrives or disk arrays or other storage (e.g., flash) as a file-systemfor data, for example. In an example, a disk array can include alltraditional hard drives, all flash drives, or a combination oftraditional hard drives and flash drives. Volumes can span a portion ofa disk, a collection of disks, or portions of disks, for example, andtypically define an overall logical arrangement of file storage on diskspace in the storage system. In one embodiment a volume can comprisestored data as one or more files that reside in a hierarchical directorystructure within the volume.

Volumes are typically configured in formats that may be associated withparticular storage systems, and respective volume formats typicallycomprise features that provide functionality to the volumes, such asproviding an ability for volumes to form clusters. For example, where afirst storage system may utilize a first format for their volumes, asecond storage system may utilize a second format for their volumes.

In the clustered network environment 100, the host devices 108, 110 canutilize the data storage systems 102, 104 to store and retrieve datafrom the volumes 132. In this embodiment, for example, the host device108 can send data packets to the network module 120 in the node 116within data storage system 102. The node 116 can forward the data to thedata storage device 128 using the disk module 124, where the datastorage device 128 comprises volume 132A. In this way, in this example,the host device can access the volume 132A, to store and/or retrievedata, using the data storage system 102 connected by the storage networkconnection 112. Further, in this embodiment, the host device 110 canexchange data with the network module 122 in the node 118 within thedata storage system 104 (e.g., which may be remote from the data storagesystem 102). The node 118 can forward the data to the data storagedevice 130 using the disk module 126, thereby accessing volume 1328associated with the data storage device 130.

It may be appreciated that replay of metadata and data operations may beimplemented within the clustered network environment 100. In an example,operations may be executed at node 116 and replayed at node 118. It maybe appreciated that replay of metadata and data operations may beimplemented for and/or between any type of computing environment, andmay be transferrable between physical devices (e.g., node 116, node 118,a desktop computer, a tablet, a laptop, a wearable device, a mobiledevice, a storage device, a server, etc.) and/or a cloud computingenvironment (e.g., remote to the clustered network environment 100).

FIG. 2 is an illustrative example of a data storage system 200 (e.g.,102, 104 in FIG. 1), providing further detail of an embodiment ofcomponents that may implement one or more of the techniques and/orsystems described herein. The data storage system 200 comprises a node202 (e.g., nodes 116, 118 in FIG. 1), and a data storage device 234(e.g., data storage devices 128, 130 in FIG. 1). The node 202 may be ageneral purpose computer, for example, or some other computing deviceparticularly configured to operate as a storage server. A host device205 (e.g., 108, 110 in FIG. 1) can be connected to the node 202 over anetwork 216, for example, to provide access to files and/or other datastored on the data storage device 234. In an example, the node 202comprises a storage controller that provides client devices, such as thehost device 205, with access to data stored within data storage device234.

The data storage device 234 can comprise mass storage devices, such asdisks 224, 226, 228 of a disk array 218, 220, 222. It will beappreciated that the techniques and systems, described herein, are notlimited by the example embodiment. For example, disks 224, 226, 228 maycomprise any type of mass storage devices, including but not limited tomagnetic disk drives, flash memory, and any other similar media adaptedto store information, including, for example, data (D) and/or parity (P)information.

The node 202 comprises one or more processors 204, a memory 206, anetwork adapter 210, a cluster access adapter 212, and a storage adapter214 interconnected by a system bus 242. The data storage system 200 alsoincludes an operating system 208 installed in the memory 206 of the node202 that can, for example, implement a Redundant Array of Independent(or Inexpensive) Disks (RAID) optimization technique to optimize areconstruction process of data of a failed disk in an array.

The operating system 208 can also manage communications for the datastorage system, and communications between other data storage systemsthat may be in a clustered network, such as attached to a cluster fabric215 (e.g., 106 in FIG. 1). Thus, the node 202, such as a network storagecontroller, can respond to host device requests to manage data on thedata storage device 234 (e.g., or additional clustered devices) inaccordance with these host device requests. The operating system 208 canoften establish one or more file systems on the data storage system 200,where a file system can include software code and data structures thatimplement a persistent hierarchical namespace of files and directories,for example. As an example, when a new data storage device (not shown)is added to a clustered network system, the operating system 208 isinformed where, in an existing directory tree, new files associated withthe new data storage device are to be stored. This is often referred toas “mounting” a file system.

In the example data storage system 200, memory 206 can include storagelocations that are addressable by the processors 204 and adapters 210,212, 214 for storing related software application code and datastructures. The processors 204 and adapters 210, 212, 214 may, forexample, include processing elements and/or logic circuitry configuredto execute the software code and manipulate the data structures. Theoperating system 208, portions of which are typically resident in thememory 206 and executed by the processing elements, functionallyorganizes the storage system by, among other things, invoking storageoperations in support of a file service implemented by the storagesystem. It will be apparent to those skilled in the art that otherprocessing and memory mechanisms, including various computer readablemedia, may be used for storing and/or executing application instructionspertaining to the techniques described herein. For example, theoperating system can also utilize one or more control files (not shown)to aid in the provisioning of virtual machines.

The network adapter 210 includes the mechanical, electrical andsignaling circuitry needed to connect the data storage system 200 to ahost device 205 over a network 216, which may comprise, among otherthings, a point-to-point connection or a shared medium, such as a localarea network. The host device 205 (e.g., 108, 110 of FIG. 1) may be ageneral-purpose computer configured to execute applications. Asdescribed above, the host device 205 may interact with the data storagesystem 200 in accordance with a client/host model of informationdelivery.

The storage adapter 214 cooperates with the operating system 208executing on the node 202 to access information requested by the hostdevice 205 (e.g., access data on a storage device managed by a networkstorage controller). The information may be stored on any type ofattached array of writeable media such as magnetic disk drives, flashmemory, and/or any other similar media adapted to store information. Inthe example data storage system 200, the information can be stored indata blocks on the disks 224, 226, 228. The storage adapter 214 caninclude input/output (I/O) interface circuitry that couples to the disksover an I/O interconnect arrangement, such as a storage area network(SAN) protocol (e.g., Small Computer System Interface (SCSI), iSCSI,hyperSCSI, Fiber Channel Protocol (FCP)). The information is retrievedby the storage adapter 214 and, if necessary, processed by the one ormore processors 204 (or the storage adapter 214 itself) prior to beingforwarded over the system bus 242 to the network adapter 210 (and/or thecluster access adapter 212 if sending to another node in the cluster)where the information is formatted into a data packet and returned tothe host device 205 over the network 216 (and/or returned to anothernode attached to the cluster over the cluster fabric 215).

In one embodiment, storage of information on disk arrays 218, 220, 222can be implemented as one or more storage volumes 230, 232 that arecomprised of a cluster of disks 224, 226, 228 defining an overalllogical arrangement of disk space. The disks 224, 226, 228 that compriseone or more volumes are typically organized as one or more groups ofRAIDs. As an example, volume 230 comprises an aggregate of disk arrays218 and 220, which comprise the cluster of disks 224 and 226.

In one embodiment, to facilitate access to disks 224, 226, 228, theoperating system 208 may implement a file system (e.g., write anywherefile system) that logically organizes the information as a hierarchicalstructure of directories and files on the disks. In this embodiment,respective files may be implemented as a set of disk blocks configuredto store information, whereas directories may be implemented asspecially formatted files in which information about other files anddirectories are stored.

Whatever the underlying physical configuration within this data storagesystem 200, data can be stored as files within physical and/or virtualvolumes, which can be associated with respective volume identifiers,such as file system identifiers (FSIDs), which can be 32-bits in lengthin one example.

A physical volume corresponds to at least a portion of physical storagedevices whose address, addressable space, location, etc. doesn't change,such as at least some of one or more data storage devices 234 (e.g., aRedundant Array of Independent (or Inexpensive) Disks (RAID system)).Typically the location of the physical volume doesn't change in that the(range of) address(es) used to access it generally remains constant.

A virtual volume, in contrast, is stored over an aggregate of disparateportions of different physical storage devices. The virtual volume maybe a collection of different available portions of different physicalstorage device locations, such as some available space from each of thedisks 224, 226, and/or 228. It will be appreciated that since a virtualvolume is not “tied” to any one particular storage device, a virtualvolume can be said to include a layer of abstraction or virtualization,which allows it to be resized and/or flexible in some regards.

Further, a virtual volume can include one or more logical unit numbers(LUNs) 238, directories 236, Qtrees 235, and files 240. Among otherthings, these features, but more particularly LUNS, allow the disparatememory locations within which data is stored to be identified, forexample, and grouped as data storage unit. As such, the LUNs 238 may becharacterized as constituting a virtual disk or drive upon which datawithin the virtual volume is stored within the aggregate. For example,LUNs are often referred to as virtual drives, such that they emulate ahard drive from a general purpose computer, while they actually comprisedata blocks stored in various parts of a volume.

In one embodiment, one or more data storage devices 234 can have one ormore physical ports, wherein each physical port can be assigned a targetaddress (e.g., SCSI target address). To represent respective volumesstored on a data storage device, a target address on the data storagedevice can be used to identify one or more LUNs 238. Thus, for example,when the node 202 connects to a volume 230, 232 through the storageadapter 214, a connection between the node 202 and the one or more LUNs238 underlying the volume is created.

In one embodiment, respective target addresses can identify multipleLUNs, such that a target address can represent multiple volumes. The I/Ointerface, which can be implemented as circuitry and/or software in thestorage adapter 214 or as executable code residing in memory 206 andexecuted by the processors 204, for example, can connect to volume 230by using one or more addresses that identify the one or more LUNs 238.

It may be appreciated that replay of metadata and data operations may beimplemented for the data storage system 200. In an example, the node 202may execute operation upon an NVRAM and replay the operations to flushthe NVRAM to storage. It may be appreciated that replay of metadata anddata operations may be implemented for and/or between any type ofcomputing environment, and may be transferrable between physical devices(e.g., node 202, host device 205, a desktop computer, a tablet, alaptop, a wearable device, a mobile device, a storage device, a server,etc.) and/or a cloud computing environment (e.g., remote to the node 202and/or the host device 205).

One embodiment of replaying metadata and data operations is illustratedby an exemplary method 300 of FIG. 3. A first computing environment(e.g., a client device, a server, a cloud computing environment, etc.)may process data operations that read data from and write data toobjects, such as files, LUNs, and other storage objects. The firstcomputing environment may also process metadata operations, such asoperations that create objects, rename objects, delete objects, setattributes for objects, and/or perform other operations upon objectssuch as files, directories, inodes, LUNs, volumes, etc. The firstcomputing environment may comprise a first file system that stores datawithin volumes or other data containers, and thus the first file systemexecutes the operations.

At 302, execution of a metadata operation is tracked to identify a setof objects that are modified by the execution of the metadata operation.The set of objects may comprise of files and/or directory inodes thatare modified by the metadata operation. In one example, execution of acreate object metadata operation is tracked to determine that the createobject metadata operation modifies a parent directory object and a newobject being created within the parent directory object by the createobject metadata operation. Thus, the set of objects are identified ascomprising the parent directory object and the new object.

In another example, execution of a link object metadata operation istracked to determine that the link object metadata operation modifies aninode object to which a new link is to be established and a new parentdirectory hosting the new link. Thus, the set of objects are identifiedas comprising the inode object and the new parent directory. In anotherexample, execution of an unlink object metadata operation is tracked todetermine that the unlink object metadata operation modifies an inodeobject from which a link is being removed and a parent directory thatwas hosting the link. Thus, the set of objects are identified ascomprising the inode object and the parent directory.

In another example, execution of a rename metadata operation is trackedto determine that the rename metadata operation modifies a firstdirectory within which a file being renamed was stored, a seconddirectory into which the file being renamed will be stored, and thefile. Thus, the set of objects are identified as comprising the firstdirectory, the second directory, and the file. If the second directorycomprises a second file having the same name as the file that will bestored within the second directory, then the tracking of the executionof the rename metadata operation will determine that the second filewill be modified because the rename metadata operation overwrites thesecond file with the file. Thus, the set of objects may also comprisethe second file.

In another example, execution of a set attribute metadata operation istracked to determine that the set attribute metadata operation modifiesan object whose attribute (e.g., a size, ownership information, etc.) isbeing set by the set attribute metadata operation. Thus, the set ofobjects are identified as comprising the object. In this way, executionof the metadata operations are tracked to determine what objects arechanged by the execution of such metadata operations.

At 304, a set of identifiers of the set of objects are stored inassociation with the metadata operation. The set of identifiers maycomprise file identifiers, directory identifiers, and volumeidentifiers. In one example, the set of identifiers are stored in a datastructure. In another example, the set of identifiers are stored withina message of the metadata operation, such as within a scratch area in amessage payload (e.g., the message may comprise the metadata operationand the scratch area, which may be stored within an NVLog for laterreplay or transmitted to a second computing device for replay as part ofa replication scheme).

In one example of metadata operation execution, the metadata operationis executed by a source file system of the first computing environment,such as upon data within a source volume. The first computingenvironment may have a replication relationship with a second computingenvironment (e.g., a second client device, a second server, a differentcomputer within the cloud environment or a different cloud environment,etc.). For example, data of the source volume may be replicated to adestination volume hosted by the second computing environment. Thereplication may occur by replicating incoming operations that arelocally executed by the source file system upon the source volume, andtransmitting the replicated operations to the second computingenvironment for replay (e.g., execution) by a destination file system ofthe second computing environment upon the destination volume. In thisway, the metadata operation may be transmitted to the second computingenvironment for replay upon the destination volume, such as forexecution by a rapid cutover engine that provides semi-synchronousreplication.

In another example of metadata operation execution, the metadataoperation may be executed upon data within an NVRAM or other type ofcache, and is logged within an NVLog of a node. The NVLog is used totrack execution of operations not yet flushed to persistent storage suchas to a disk drive, but instead are executed within the NVRAM as part ofa caching technique. When a replay triggering event occurs (e.g., thenode panics, the node is taken over by a high availability partner node,the node boots up, etc.), the operations tracked within the NVLog arereplayed.

At 306, a determination is made that the metadata operation is to bereplayed for a target file system. In one example where the metadataoperation was logged into the NVLog and executed against the NVRAM,replay of the metadata operation from the NVLog to flush the contents ofthe NVRAM to storage is determined based upon an occurrence of thereplay triggering event. The replay triggering event corresponds toNVLog replay post panic of the node, such as when the high availabilitypartner node takes over or the node reboots after the panic.

In another example where the metadata operation was executed upon thesource volume hosted by the first computing environment and wasreplicated to the second computing environment for replay (execution)upon the destination volume, replay of the metadata operation istriggered based upon various trigger conditions. For example, receipt ofthe metadata operation by the second computing environment triggers thereplay of the metadata operation. In another example, replicatedoperations may be queued, such as by a replication cutover engine thatimplements semi-synchronous replication for the second computingenvironment, into a replication queue. Operations may be dequeued andreplayed from the replication queue.

At 308, a tracking data structure is queried using the set ofidentifiers of the set of objects that were modified by the initialexecution of the metadata operation to determine whether the metadataoperation is independent or dependent with respect to pending operationsalready dispatched to the target file system for execution (replay). Thetracking data structure is used to track identifiers of objects thatwill be modified by operations dispatched, such as from the NVLog orreplication queue, to the target file system for replay (execution). Ifthe set of identifiers do not match any identifiers within the trackingdata structure, then the metadata operation is independent of pendingoperations already dispatched to the target file system, and thus willnot modify objects being modified by the pending operations.Accordingly, the metadata operation is dispatched to the target filesystem for replay, at 310. In this way, the metadata operation can beexecuted in parallel with the pending operations without having to waitfor the pending operations to complete first. This significantlyimproves the speed of replay and utilization of resources by executingmetadata operations in parallel with other operations. At the time ofdispatching the metadata operation to the target file system, the set ofidentifiers are populated into the tracking data structure to indicatethat the set of objects will be modified by the metadata operation.

If at least one identifier within the set of identifiers matches atleast one identifier within the tracking data structure, then themetadata operation is dependent upon one or more pending operationsalready dispatched to the target file system, and thus will modify atleast one object that will be modified by the one or more pendingoperations. Accordingly, replay of the metadata operation is withheld,at 312. In one example, the metadata operation may be requeued andevaluated later, such as after a threshold amount of time, to see if themetadata operation can be replayed. In another example, the metadataoperation is serially dispatched to the target file system for replayafter the pending operations have been complete. In this way, thedestination volume will be consistent with the source volume becauseobjects are modified at the destination volume in the same order theobjects were modified at the source volume.

Similarly, data operations may be replayed either in parallel orserially with respect to pending operations already dispatched to thetarget file system. For example, a determination is made that a dataoperation is to be replayed for the target file system (e.g., the dataoperation may be logged within the NVLog and must be replayed from theNVLog to storage or may be queued within the replication queue forexecution upon the destination volume). The data operation is evaluatedto identify an object (e.g., a file that is being written to) that willbe modified by the replay of the data operation. The tracking datastructure is queried using an identifier of the object. If theidentifier does not match any identifiers within the tracking datastructure, then the data operation is dispatched to the target filesystem for replay. The tracking data structure is populated with theidentifier to indicate that the object will be modified by the dataoperation dispatched to the target file system for replay. For example,the data operation is serially dispatched to the target file system forexecution after the pending dispatched operations are complete.

In one example where a set of operations are to be replayed for thetarget file system, identifiers of objects that were modified by the setof operations during an initial execution (e.g., execution upon theNVRAM or the source volume) and the tracking data structure are used toidentify operations that are dependent upon one another and operationsthat are independent of one another. In this way, dependent operationsare dispatched to the target file system for serial execution in anorder of which the dependent operations were initially executed. Theorder of execution may be preserved using sequence numbers assigned toeach operation to indicate the order each operation was executed duringthe initial execution. Independent operations are dispatched to thetarget file system for parallel execution.

FIG. 4 illustrates an example of a system 400 for replaying metadata anddata operations. A computing device may comprise an NVRAM 402 that isused for caching, such as for caching of modify operations. Inparticular, operations, such as write operations, metadata operations,and/or other types of modify operations, are cached within the NVRAM 402and logged within an NVLog. In this way, the operations are initiallyexecuted upon the NVRAM 402. At an occurrence of a replay triggeringevent (e.g., the node rebooting after a system panic or a highavailability partner node taking over for the node due to the systempanic), the cached operations are replayed to storage (e.g., flushed topersistent storage).

In one example of initially executing (e.g., caching) operations, afirst operation 404 to create a file (1) within a directory (1) isreceived and executed upon the NVRAM 402. The execution of the firstoperation 404 is tracked to determine that the file (1) and thedirectory (1) are modified by the execution of the first operation 404.Accordingly, a first set of identifiers 406 comprising a file (1)identifier and a directory (1) identifier are stored in association withthe first operation 404. A second operation 408 to resize a file (2)that is stored within a directory (2) is received and executed upon theNVRAM 402. The execution of the second operation 408 is tracked todetermine that the file (2) and the directory (2) are modified by theexecution of the second operation 408. Accordingly, a second set ofidentifiers 410 comprising a file (2) identifier and a directory (2)identifier are stored in association with the second operation 408.

A third operation 412 to create a file (3) within a directory (3) isreceived and executed upon the NVRAM 402. The execution of the thirdoperation 412 is tracked to determine that the file (3) and thedirectory (3) are modified by the execution of the third operation 412.Accordingly, a third set of identifiers 414 comprising a file (3)identifier and a directory (3) identifier are stored in association withthe third operation 412. A fourth operation 416 to write data to thefile (1) within the directory (1) is received and executed upon theNVRAM 402. The execution of the fourth operation 416 is tracked todetermine that the file (1) and the directory (1) are modified by theexecution of the fourth operation 416. Accordingly, a fourth set ofidentifiers 418 comprising the file (1) identifier and the directory (1)identifier are stored in association with the fourth operation 416.

A fifth operation 420 to write data to the file (3) within the directory(3) is received and executed upon the NVRAM 402. The execution of thefifth operation 420 is tracked to determine that the file (3) and thedirectory (3) are modified by the execution of the fifth operation 420.Accordingly, a fifth set of identifiers 422 comprising the file (3)identifier and the directory (3) identifier are stored in associationwith the fifth operation 420. A sixth operation 424 to write data to theresized file (2) within the directory (2) is received and executed uponthe NVRAM 402. The execution of the sixth operation 424 is tracked todetermine that the file (2) and the directory (2) are modified by theexecution of the sixth operation 424. Accordingly, a sixth set ofidentifiers 426 comprising the file (2) identifier and the directory (2)identifier are stored in association with the sixth operation 424.

During replay of the operations by a target file system 428 to flush theNVRAM 402 to a storage device 430, the sets of identifiers are evaluatedto determine what operations can be replayed/executed in parallel andwhat operations are to be replayed/executed serially with respect to oneanother. For example, the first operation 404, the second operation 408,and the third operation 412 are independent of one another because thereis no overlap of what objects will be modified by the first operation404, the second operation 408, and the third operation 412. Accordingly,the first operation 404, the second operation 408, and the thirdoperation 412 can be replayed in parallel with respect to one another.

The fourth operation 416 is dependent upon the first operation 404, andthus the fourth operation 416 will be withheld from being replayed untilthe first operation 404 is complete because the first operation 404 mustfirst create the file (1) before the file (1) can be written to by thefourth operation 416. The sixth operation 424 is dependent upon thesecond operation 408, and thus the sixth operation 424 will be withheldfrom being replayed until the second operation 408 is complete becausethe second operation 408 must first resize the file (2) before the sixthoperation 424 can write to the resized file (2). The fifth operation 420is dependent upon the third operation 412, and thus the fifth operation420 will be withheld from being replayed until the third operation 412is complete because the third operation 412 must first create the file(3) before the file (3) can be written to by the fifth operation 420.The fourth operation 416, the fifth operation 420, and the sixthoperation 424 are independent of one another because there is no overlapof what objects will be modified by the fourth operation 416, the fifthoperation 420, and the sixth operation 424. Accordingly, the fourthoperation 416, the fifth operation 420, and the sixth operation 424 canbe replayed in parallel with respect to one another. In this way, theoperations are dispatched to the target file system 428 in a manner(e.g., some serially and/or some in parallel) that preserves the orderwith which objects were modified when the operations were initiallyexecuted upon the NVRAM 402. In this way, a state of the storage device430 (e.g., what data is stored, a directory structure, names of objects,etc.) is consistent with a state of the NVRAM 402.

FIG. 5 illustrates an example of a system 500 for replaying metadata anddata operations. A first computing device 526 may have a replicationrelationship (e.g., a semi-synchronous replication relationship, asynchronous replication relationship, etc.) with a second computingdevice 530. For example, data of a source volume hosted by the firstcomputing device 526 may be replicated to a destination volume hosted bythe second computing device 530 by replicating incoming operations thatare executed upon the source volume to the second computing device 530for execution upon the destination volume by a target file system 524.

In one example, a create object operation 504 is executed by the firstcomputing device 526 upon the source volume. The execution is tracked toidentify a set of identifiers (1) 506 of objects modified by theexecution of the create object operation 504. A link object operation508 is executed by the first computing device 526 upon the sourcevolume. The execution is tracked to identify a set of identifiers (2)510 of objects modified by the execution of the link object operation508. An unlink object operation 512 is executed by the first computingdevice 526 upon the source volume. The execution is tracked to identifya set of identifiers (3) 514 of objects modified by the execution of theunlink object operation 512. A rename operation 516 is executed by thefirst computing device 526 upon the source volume. The execution istracked to identify a set of identifiers (4) 518 of objects modified bythe execution of the rename operation 516. A set attribute operation 520is executed by the first computing device 526 upon the source volume.The execution is tracked to identify a set of identifiers (5) 522 ofobjects modified by the execution of the set attribute operation 520.

The first computing device 526 replicates the operations, and transmits528 the replicated operations and the sets of identifiers to the secondcomputing device 530 for replay by the target file system 524. The setsof identifiers are evaluated to determine which operations can bereplayed in parallel with respect to one another and which operationsare to be replayed serially with respect to one another (determine whichoperations are dependent on other operations completing first). In thisway, some operations may be dispatched to the target file system 524 forparallel execution while other operations may be dispatched to thetarget file system 524 for serial execution.

Still another embodiment involves a computer-readable medium comprisingprocessor-executable instructions configured to implement one or more ofthe techniques presented herein. An example embodiment of acomputer-readable medium or a computer-readable device that is devisedin these ways is illustrated in FIG. 6, wherein the implementation 600comprises a computer-readable medium 608, such as a compactdisc-recordable (CD-R), a digital versatile disc-recordable (DVD-R),flash drive, a platter of a hard disk drive, etc., on which is encodedcomputer-readable data 606. This computer-readable data 606, such asbinary data comprising at least one of a zero or a one, in turncomprises a processor-executable computer instructions 604 configured tooperate according to one or more of the principles set forth herein. Insome embodiments, the processor-executable computer instructions 604 areconfigured to perform a method 602, such as at least some of theexemplary method 300 of FIG. 3, for example. In some embodiments, theprocessor-executable computer instructions 604 are configured toimplement a system, such as at least some of the exemplary system 400 ofFIG. 4 and/or at least some of the exemplary system 500 of FIG. 5, forexample. Many such computer-readable media are contemplated to operatein accordance with the techniques presented herein.

FIG. 7 is a diagram illustrating an example operating environment 700 inwhich an embodiment of the techniques described herein may beimplemented. In one example, the techniques described herein may beimplemented within a client device 728, such as a laptop, tablet,personal computer, mobile device, wearable device, etc. In anotherexample, the techniques described herein may be implemented within astorage controller 730, such as a node configured to manage the storageand access to data on behalf of the client device 728 and/or otherclient devices. In another example, the techniques described herein maybe implemented within a distributed computing platform 702 such as acloud computing environment (e.g., a cloud storage environment, amulti-tenant platform, etc.) configured to manage the storage and accessto data on behalf of the client device 728 and/or other client devices.

In yet another example, at least some of the techniques described hereinare implemented across one or more of the client device 728, the storagecontroller 730, and the distributed computing platform 702. For example,the client device 728 may transmit operations, such as data operationsto read data and write data and metadata operations (e.g., a create fileoperation, a rename directory operation, a resize operation, a setattribute operation, etc.), over a network 726 to the storage controller730 for implementation by the storage controller 730 upon storage. Thestorage controller 730 may store data associated with the operationswithin volumes or other data objects/structures hosted within locallyattached storage, remote storage hosted by other computing devicesaccessible over the network 726, storage provided by the distributedcomputing platform 702, etc. The storage controller 730 may replicatethe data and/or the operations to other computing devices so that one ormore replicas, such as a destination storage volume that is maintainedas a replica of a source storage volume, are maintained. Such replicascan be used for disaster recovery and failover.

The storage controller 730 may store the data or a portion thereofwithin storage hosted by the distributed computing platform 702 bytransmitting the data to the distributed computing platform 702. In oneexample, the storage controller 730 may locally store frequentlyaccessed data within locally attached storage. Less frequently accesseddata may be transmitted to the distributed computing platform 702 forstorage within a data storage tier 708. The data storage tier 708 maystore data within a service data store 720, and may store clientspecific data within client data stores assigned to such clients such asa client (1) data store 722 used to store data of a client (1) and aclient (N) data store 724 used to store data of a client (N). The datastores may be physical storage devices or may be defined as logicalstorage, such as a virtual volume, LUNs, or other logical organizationsof data that can be defined across one or more physical storage devices.In another example, the storage controller 730 transmits and stores allclient data to the distributed computing platform 702. In yet anotherexample, the client device 728 transmits and stores the data directly tothe distributed computing platform 702 without the use of the storagecontroller 730.

The management of storage and access to data can be performed by one ormore storage virtual machines (SMVs) or other storage applications thatprovide software as a service (SaaS) such as storage software services.In one example, an SVM may be hosted within the client device 728,within the storage controller 730, or within the distributed computingplatform 702 such as by the application server tier 706. In anotherexample, one or more SVMs may be hosted across one or more of the clientdevice 728, the storage controller 730, and the distributed computingplatform 702.

In one example of the distributed computing platform 702, one or moreSVMs may be hosted by the application server tier 706. For example, aserver (1) 716 is configured to host SVMs used to execute applicationssuch as storage applications that manage the storage of data of theclient (1) within the client (1) data store 722. Thus, an SVM executingon the server (1) 716 may receive data and/or operations from the clientdevice 728 and/or the storage controller 730 over the network 726. TheSVM executes a storage application to process the operations and/orstore the data within the client (1) data store 722. The SVM maytransmit a response back to the client device 728 and/or the storagecontroller 730 over the network 726, such as a success message or anerror message. In this way, the application server tier 706 may hostSVMs, services, and/or other storage applications using the server (1)716, the server (N) 718, etc.

A user interface tier 704 of the distributed computing platform 702 mayprovide the client device 728 and/or the storage controller 730 withaccess to user interfaces associated with the storage and access of dataand/or other services provided by the distributed computing platform702. In an example, a service user interface 710 may be accessible fromthe distributed computing platform 702 for accessing services subscribedto by clients and/or storage controllers, such as data replicationservices, application hosting services, data security services, humanresource services, warehouse tracking services, accounting services,etc. For example, client user interfaces may be provided tocorresponding clients, such as a client (1) user interface 712, a client(N) user interface 714, etc. The client (1) can access various servicesand resources subscribed to by the client (1) through the client (1)user interface 712, such as access to a web service, a developmentenvironment, a human resource application, a warehouse trackingapplication, and/or other services and resources provided by theapplication server tier 706, which may use data stored within the datastorage tier 708.

The client device 728 and/or the storage controller 730 may subscribe tocertain types and amounts of services and resources provided by thedistributed computing platform 702. For example, the client device 728may establish a subscription to have access to three virtual machines, acertain amount of storage, a certain type/amount of data redundancy, acertain type/amount of data security, certain service level agreements(SLAs) and service level objectives (SLOs), latency guarantees,bandwidth guarantees, access to execute or host certain applications,etc. Similarly, the storage controller 730 can establish a subscriptionto have access to certain services and resources of the distributedcomputing platform 702.

As shown, a variety of clients, such as the client device 728 and thestorage controller 730, incorporating and/or incorporated into a varietyof computing devices may communicate with the distributed computingplatform 702 through one or more networks, such as the network 726. Forexample, a client may incorporate and/or be incorporated into a clientapplication (e.g., software) implemented at least in part by one or moreof the computing devices.

Examples of suitable computing devices include personal computers,server computers, desktop computers, nodes, storage servers, storagecontrollers, laptop computers, notebook computers, tablet computers orpersonal digital assistants (PDAs), smart phones, cell phones, andconsumer electronic devices incorporating one or more computing devicecomponents, such as one or more electronic processors, microprocessors,central processing units (CPU), or controllers. Examples of suitablenetworks include networks utilizing wired and/or wireless communicationtechnologies and networks operating in accordance with any suitablenetworking and/or communication protocol (e.g., the Internet). In usecases involving the delivery of customer support services, the computingdevices noted represent the endpoint of the customer support deliveryprocess, i.e., the consumer's device.

The distributed computing platform 702, such as a multi-tenant businessdata processing platform or cloud computing environment, may includemultiple processing tiers, including the user interface tier 704, theapplication server tier 706, and a data storage tier 708. The userinterface tier 704 may maintain multiple user interfaces, includinggraphical user interfaces and/or web-based interfaces. The userinterfaces may include the service user interface 710 for a service toprovide access to applications and data for a client (e.g., a “tenant”)of the service, as well as one or more user interfaces that have beenspecialized/customized in accordance with user specific requirements,which may be accessed via one or more APIs.

The service user interface 710 may include components enabling a tenantto administer the tenant's participation in the functions andcapabilities provided by the distributed computing platform 702, such asaccessing data, causing execution of specific data processingoperations, etc. Each processing tier may be implemented with a set ofcomputers, virtualized computing environments such as a storage virtualmachine or storage virtual server, and/or computer components includingcomputer servers and processors, and may perform various functions,methods, processes, or operations as determined by the execution of asoftware application or set of instructions.

The data storage tier 708 may include one or more data stores, which mayinclude the service data store 720 and one or more client data stores.Each client data store may contain tenant-specific data that is used aspart of providing a range of tenant-specific business and storageservices or functions, including but not limited to ERP, CRM, eCommerce,Human Resources management, payroll, storage services, etc. Data storesmay be implemented with any suitable data storage technology, includingstructured query language (SQL) based relational database managementsystems (RDBMS), file systems hosted by operating systems, objectstorage, etc.

In accordance with one embodiment of the invention, the distributedcomputing platform 702 may be a multi-tenant and service platformoperated by an entity in order to provide multiple tenants with a set ofbusiness related applications, data storage, and functionality. Theseapplications and functionality may include ones that a business uses tomanage various aspects of its operations. For example, the applicationsand functionality may include providing web-based access to businessinformation systems, thereby allowing a user with a browser and anInternet or intranet connection to view, enter, process, or modifycertain types of business information or any other type of information.

In another embodiment, the described methods and/or their equivalentsmay be implemented with computer executable instructions. Thus, in oneembodiment, a non-transitory computer readable/storage medium isconfigured with stored computer executable instructions of analgorithm/executable application that when executed by a machine(s)cause the machine(s) (and/or associated components) to perform themethod. Example machines include but are not limited to a processor, acomputer, a server operating in a cloud computing system, a serverconfigured in a Software as a Service (SaaS) architecture, a smartphone, and so on). In one embodiment, a computing device is implementedwith one or more executable algorithms that are configured to performany of the disclosed methods.

It will be appreciated that processes, architectures and/or proceduresdescribed herein can be implemented in hardware, firmware and/orsoftware. It will also be appreciated that the provisions set forthherein may apply to any type of special-purpose computer (e.g., filehost, storage server and/or storage serving appliance) and/orgeneral-purpose computer, including a standalone computer or portionthereof, embodied as or including a storage system. Moreover, theteachings herein can be configured to a variety of storage systemarchitectures including, but not limited to, a network-attached storageenvironment and/or a storage area network and disk assembly directlyattached to a client or host computer. Storage system should thereforebe taken broadly to include such arrangements in addition to anysubsystems configured to perform a storage function and associated withother equipment or systems.

In some embodiments, methods described and/or illustrated in thisdisclosure may be realized in whole or in part on computer-readablemedia. Computer readable media can include processor-executableinstructions configured to implement one or more of the methodspresented herein, and may include any mechanism for storing this datathat can be thereafter read by a computer system. Examples of computerreadable media include (hard) drives (e.g., accessible via networkattached storage (NAS)), Storage Area Networks (SAN), volatile andnon-volatile memory, such as read-only memory (ROM), random-accessmemory (RAM), electrically erasable programmable read-only memory(EEPROM) and/or flash memory, compact disk read only memory (CD-ROM)s,CD-Rs, compact disk re-writeable (CD-RW)s, DVDs, cassettes, magnetictape, magnetic disk storage, optical or non-optical data storage devicesand/or any other medium which can be used to store data.

Although the subject matter has been described in language specific tostructural features or methodological acts, it is to be understood thatthe subject matter defined in the appended claims is not necessarilylimited to the specific features or acts described above. Rather, thespecific features and acts described above are disclosed as exampleforms of implementing at least some of the claims.

Various operations of embodiments are provided herein. The order inwhich some or all of the operations are described should not beconstrued to imply that these operations are necessarily orderdependent. Alternative ordering will be appreciated given the benefit ofthis description. Further, it will be understood that not all operationsare necessarily present in each embodiment provided herein. Also, itwill be understood that not all operations are necessary in someembodiments.

Furthermore, the claimed subject matter is implemented as a method,apparatus, or article of manufacture using standard application orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer application accessible from anycomputer-readable device, carrier, or media. Of course, manymodifications may be made to this configuration without departing fromthe scope or spirit of the claimed subject matter.

As used in this application, the terms “component”, “module,” “system”,“interface”, and the like are generally intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentincludes a process running on a processor, a processor, an object, anexecutable, a thread of execution, an application, or a computer. By wayof illustration, both an application running on a controller and thecontroller can be a component. One or more components residing within aprocess or thread of execution and a component may be localized on onecomputer or distributed between two or more computers.

Moreover, “exemplary” is used herein to mean serving as an example,instance, illustration, etc., and not necessarily as advantageous. Asused in this application, “or” is intended to mean an inclusive “or”rather than an exclusive “or”. In addition, “a” and “an” as used in thisapplication are generally be construed to mean “one or more” unlessspecified otherwise or clear from context to be directed to a singularform. Also, at least one of A and B and/or the like generally means A orB and/or both A and B. Furthermore, to the extent that “includes”,“having”, “has”, “with”, or variants thereof are used, such terms areintended to be inclusive in a manner similar to the term “comprising”.

Many modifications may be made to the instant disclosure withoutdeparting from the scope or spirit of the claimed subject matter. Unlessspecified otherwise, “first,” “second,” or the like are not intended toimply a temporal aspect, a spatial aspect, an ordering, etc. Rather,such terms are merely used as identifiers, names, etc. for features,elements, items, etc. For example, a first set of information and asecond set of information generally correspond to set of information Aand set of information B or two different or two identical sets ofinformation or the same set of information.

Also, although the disclosure has been shown and described with respectto one or more implementations, equivalent alterations and modificationswill occur to others skilled in the art based upon a reading andunderstanding of this specification and the annexed drawings. Thedisclosure includes all such modifications and alterations and islimited only by the scope of the following claims. In particular regardto the various functions performed by the above described components(e.g., elements, resources, etc.), the terms used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent (e.g., that is functionally equivalent), even though notstructurally equivalent to the disclosed structure. In addition, while aparticular feature of the disclosure may have been disclosed withrespect to only one of several implementations, such feature may becombined with one or more other features of the other implementations asmay be desired and advantageous for any given or particular application.

What is claimed is:
 1. A method comprising: identifying a set of objectsthat will be modified by execution of an operation; storing identifiersof the set of objects within a tracking structure used to track objectsbeing modified by operations dispatched to a target file system;dispatching the operation to the target file system for execution; andin response to determining that the operation was successfully executedby the target file system, removing the identifiers of the set ofobjects from the tracking structure.
 2. The method of claim 1,comprising: receiving a metadata operation to execute; identifying anidentifier of an object that will be modified by execution of themetadata operation; and in response to the identifier occurring withinthe tracking structure, withholding dispatch of the metadata operationto the target file system for execution.
 3. The method of claim 1,comprising: receiving a metadata operation to execute; identifying anidentifier of an object that will be modified by execution of themetadata operation; and in response to the identifier not occurringwithin the tracking structure, dispatching the metadata operation to thetarget file system for execution.
 4. The method of claim 1, comprising:receiving a metadata operation to execute; identifying a firstidentifier of a first object and a second identifier of a second objectthat will be modified by execution of the metadata operation; and inresponse to the first identifier occurring within the tracking structureand the second identifier not occurring within the tracking structure,withholding dispatch of the metadata operation to the target file systemfor execution.
 5. The method of claim 1, comprising: withholdingdispatch of a metadata operation based upon the metadata operationmodifying an object having an identifier tracked within the trackingstructure; and in response to the identifier being removed from thetracking structure, dispatching the metadata to the target file systemfor execution.
 6. The method of claim 1, comprising: in response to anidentifier of an object being modified by a metadata operation occurringwithin the tracking structure, determining that the metadata operationis depending upon at least one operation dispatched to the target filesystem.
 7. The method of claim 1, comprising: in response to identifiersof objects being modified by a metadata operation not occurring withinthe tracking structure, determining that the metadata operation isindependent of operations dispatched to the target file system.
 8. Themethod of claim 1, comprising: performing an initial execution of theoperation to identify the set of objects modified by the operation. 9.The method of claim 1, comprising: caching the operation within anon-volatile log (NVLog) to identify the set of objects modified by theoperation.
 10. The method of claim 1, comprising: utilizing the trackingstructure to identify dependent operations; and serially dispatching thedependent operations to the target file system for execution.
 11. Themethod of claim 1, comprising: utilizing the tracking structure toidentify independent operations; and dispatching the independentoperations to the target file system in parallel for execution.
 12. Themethod of claim 1, wherein the operation comprises a rename metadataoperation to rename a file as a renamed file, and the method comprises:identifying the set of objects as a first directory within which thefile is currently stored, a second directory into which the renamed filewill be stored by the rename metadata operation, and the file beingrenamed.
 13. A computing device comprising: a memory comprising machineexecutable code; and a processor coupled to the memory, the processorconfigured to execute the machine executable code to cause the processorto: identify a set of objects that will be modified by execution of afirst operation; store identifiers of the set of objects within atracking structure used to track objects being modified by operationsdispatched to a target file system; dispatch the first operation to thetarget file system for execution; and in response to a second operationmodifying an object having an identifier tracked within the trackingstructure, withhold dispatch of the second operation to the target filesystem.
 14. The computing device of claim 13, wherein the machineexecutable code causes the processor to: in response to determining thatthe identifier is no longer tracked within the tracking structure,dispatch the second operation to the target file system.
 15. Thecomputing device of claim 13, wherein the machine executable code causesthe processor to: in response to determining that the first operationwas successfully executed by the target file system, remove theidentifiers of the set of objects from the tracking structure.
 16. Thecomputing device of claim 13, wherein the machine executable code causesthe processor to: utilize the tracking structure to identify dependentoperations; and serially dispatch the dependent operations to the targetfile system for execution.
 17. The computing device of claim 13, whereinthe machine executable code causes the processor to: utilize thetracking structure to identify independent operations; and dispatch theindependent operations to the target file system in parallel forexecution.
 18. A non-transitory machine readable medium comprisinginstructions for performing a method, which when executed by a machine,causes the machine to: identify a set of objects that will be modifiedby execution of a first operation; store identifiers of the set ofobjects within a tracking structure used to track objects being modifiedby operations dispatched to a target file system; dispatch the firstoperation to the target file system for execution; and in response todetermining that the first operation was successfully executed by thetarget file system, remove the identifiers of the set of objects fromthe tracking structure.
 19. The non-transitory machine readable mediumof claim 18, wherein the instructions cause the machine to: in responseto a second operation modifying an object having an identifier trackedwithin the tracking structure, withhold dispatch of the second operationto the target file system.
 20. The non-transitory machine readablemedium of claim 18, wherein the instructions cause the machine to:perform an initial execution of the operation into a cache to identifythe set of objects modified by the operation.